Key Responsibilities:
· Architect and develop a multi-agent AI framework where autonomous agents coordinate to solve domain-specific technical queries.
· Leverage LLMs, NLP, and tool-based reasoning to automate data extraction, analysis, and insight generation.
· Build agents capable of integrating with engineering tools, simulators, databases, and knowledge sources.
· Collaborate with domain experts to align agent behavior with technical expectations and constraints.
· Implement safeguards to ensure accuracy, traceability, and reliability of AI-generated outputs.
· Continuously optimize prompting, agent orchestration, and performance under real-world conditions.
Required Skills and Experience:
· Demonstrated expertise in building Agentic AI architectures, using frameworks like LangChain, AutoGen, CrewAI, or custom stacks.
· Strong foundation in LLM-based NLP, prompt engineering, and context-aware reasoning.
· Advanced Python programming and experience deploying AI workflows in cloud or containerized environments.
· Ability to work with APIs, data models, and external toolchains across complex systems.
· Comfortable operating independently with minimal supervision in a cross-functional environment.
Nice to Have:
· Exposure to industrial domains such as energy, manufacturing, or heavy engineering.
· Understanding of vector databases, knowledge graphs, and retrieval-augmented generation.
· Familiarity with Azure or AWS development environments.
Certifications:
· Azure AI Engineer or Azure Data Engineer certification is a plus.
· AWS experience is nice to have, but not required.
Industry Experience:
· Oil and gas domain experience is a strong advantage, especially familiarity with digital operations or engineering workflows.
Pay: Up to ₹3,000,000.00 per year
Benefits:
Work Location: Hybrid remote in Pune, Maharashtra (Pune)
